Rrw a robust and reversible watermarking technique for relational

Advancement in information technology is playing an increasing role in the use of information systems comprising relational databases. These databases are used effectively in collaborative environments for information extraction; consequently, they are vulnerable to security threats concerning ownership rights and data tampering.

Rrw a robust and reversible watermarking technique for relational

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RRW - A ROBUST AND REVERSIBLE WATERMARKING TECHNIQUE FOR
RELATIONAL DATA
ABSTRACT:
Advancement in information technology is playing an increasing role in the use of
information systems comprising relational databases. These databases are used effectively in
collaborative environments for information extraction; consequently, they are vulnerable to
security threats concerning ownership rights and data tampering. Watermarking is advocated to
enforce ownership rights over shared relational data and for providing a means for tackling data
tampering. When ownership rights are enforced using watermarking, the underlying data
undergoes certain modifications; as a result of which, the data quality gets compromised.
Reversible watermarking is employed to ensure data quality along-with data recovery. However,
such techniques are usually not robust against malicious attacks and do not provide any
mechanism to selectively watermark a particular attribute by taking into account its role in
knowledge discovery. Therefore, reversible watermarking is required that ensures; (i) watermark
encoding and decoding by accounting for the role of all the features in knowledge discovery;
and, (ii) original data recovery in the presence of active malicious attacks. In this paper, a robust
and semiblind reversible watermarking (RRW) technique for numerical relational data has been
proposed that addresses the above objectives. Experimental studies prove the effectiveness of
RRW against malicious attacks and show that the proposed technique outperforms existing ones.

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1.
#13/ 19, 1st Floor, Municipal Colony, Kangayanellore Road, Gandhi Nagar, vellore – 6.
Off: 0416-2247353 / 6066663 Mo: +91 9500218218 /8870603602,
Project Titles: http://shakastech.weebly.com/2015-2016-titles
Website: www.shakastech.com, Email - id: shakastech@gmail.com, info@shakastech.com
EXISTING SYSTEM:
Relational data in particular is shared extensively by the owners with research
communities and in virtual data storage locations in the Cloud. The purpose is to work in a
collaborative environment and make data openly available so that it is useful for knowledge
extraction and decision making. Take the case of Walmart- a large multinational retail
corporation that has made its sales database available openly over the Internet so that it may be
used for the purposes of identifying market trends through data mining.
PROPOSED SYSTEM:
Technique that keeps the data useful for knowledge discovery. Data modifications are
allowed to such extent that the quality of the data before embedding watermark information and
after extracting is acceptable for knowledge extraction process. Consequently, knowledge
discovery becomes successful in decision support systems where high quality data recovery is
imperative. Reversible watermarking techniques are already available in literature; however, to
the best of our knowledge, no work has been conducted on overcoming the problems of
reversible watermarking techniques in the presence of malicious attacks. Achieving robustness
(attack resilience) in the presence of reversibility (ability to recover the watermark and the
original data) is a challenging task.